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41 - 50 of 1,000 search results for :pc53 24 / |u:mi.eng.cam.ac.uk where 0 match all words and 1,000 match some words.

  1. Results that match 1 of 2 words

  2. Phrase-based Statistical Language Generation usingGraphical Models…

    mi.eng.cam.ac.uk/~sjy/papers/mgjk10.pdf
    20 Feb 2018: Com-puter Speech & Language, 24(4):562–588, 2010. Y. Tokuda, T. Yoshimura, T. ... Computer Speech and Language,24(2):150–174, 2010.

  3. crosseval_diff-reward2b.ps

    mi.eng.cam.ac.uk/~sjy/papers/kgjm10.pdf
    20 Feb 2018: Yu. 2009. The Hidden InformationState model: a practical framework for POMDPbased spoken dialogue management.ComputerSpeech and Language, 24(2):150–174.

  4. On-line Active Reward Learning for Policy Optimisationin Spoken…

    mi.eng.cam.ac.uk/~sjy/papers/sgmb16.pdf
    20 Feb 2018: Thomson and Young2010] Blaise Thomson and SteveYoung. 2010. Bayesian update of dialogue state:A pomdp framework for spoken dialogue systems.Computer Speech and Language, 24:562–588.

  5. DISCRIMINATIVE SPOKEN LANGUAGE UNDERSTANDINGUSING WORD CONFUSION…

    mi.eng.cam.ac.uk/~sjy/papers/hgtt12.pdf
    20 Feb 2018: 24, no. 4, Oct. 2010. [16] S. J. Young, G. Evermann, M.

  6. From Discontinuous To Continuous F0 Modelling In HMM-based…

    mi.eng.cam.ac.uk/~sjy/papers/yuty10.pdf
    20 Feb 2018: The feature set includes 24 spectralcoefficients, log F0 and 5 aperiodic component features.

  7. A Benchmarking Environment for ReinforcementLearning Based Task…

    mi.eng.cam.ac.uk/~sjy/papers/cbsm17.pdf
    20 Feb 2018: In Proceedings of ACL, 2017. [24] Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gašić, Pei-Hao Su, DavidVandyke, Tsung-Hsien Wen, and Steve Young. ... Computer Speech & Language, 24(2):150–174, 2010. [53] Steve Young, Milica

  8. Bayesian update of dialogue state: A POMDP framework for spoken…

    mi.eng.cam.ac.uk/~sjy/papers/thyo10.pdf
    20 Feb 2018: 564 B. Thomson, S. Young / Computer Speech and Language 24 (2010) 562–588. ... B. Thomson, S. Young / Computer Speech and Language 24 (2010) 562–588 565.

  9. STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES…

    mi.eng.cam.ac.uk/~mjfg/vandalen_ASRU15.pdf
    12 Jul 2016: MPE— 7.15 11.06 14.37 24.54 16.79CML 6.95 11.00 14.29 24.39 16.68large-margin 7.02 10.92 14.16 24.28 ... Therefore the systems use graphemic lex-ica generated using an approach which is applicable to all Unicodecharacters [24].

  10. yeyo06.dvi

    mi.eng.cam.ac.uk/~sjy/papers/yeyo06.pdf
    20 Feb 2018: g(i)jq =. T. t=1. v(t)ii d. (t)jq j, q = 1, , (d 1) (24). ... Markel,”Distance measures for speech processing”,IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.ASSP-24, no.5, pp.380-391, October 1976.

  11. Practicable Assessment of Cochlear Sizeand Shape from Clinical CT ...

    mi.eng.cam.ac.uk/reports/svr-ftp/gee_tr004.pdf
    27 Jul 2020: CBCT non-planarity 2.47 2.46 3.35 15.7 16.0 14.8 12.1 10.8 8.63reach 9.36 9.16 9.57 26.7 24.7 ... MDCT non-planarity 3.04 3.67 4.52 15.1 14.2 15.5 11.7 10.6 8.3reach 13.6 11.2 10.4 26.3 24.1

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